Estimation of sleep stages in a healthy adult population from optical plethysmography and accelerometer signals
Estimation of sleep stages in a healthy adult population from optical plethysmography and accelerometer signals
复制标题
DOI：
10.1088/1361-6579/aa9047
复制
发表时间：
2017-11-01
影响因子：
3.2
通讯作者：
Heneghan, C.
中科院分区：
文献类型：
--
作者：
Beattie, Z.;Oyang, Y.;Heneghan, C.
目的：报道一种使用3D加速度计和光脉冲光体积描记器(PPG)测量运动的腕式设备估计睡眠阶段的准确性。方法：60名成年受试者在左右手腕上佩戴这些设备，同时使用包括用于睡眠分期的脑电通道的III型家庭睡眠测试设备(Embletta MPR)获得过夜录音。60例患者均为自行报告的睡眠正常者(男性36例，女性24例，年龄34+/-10岁，体重指数28+/-6岁)。Embletta的记录使用AASM指南对睡眠阶段进行评分，并用于开发和验证自动睡眠阶段估计算法，该算法将睡眠阶段标记为觉醒、轻度(N1或N2)、深度(N3)和快速眼动(REM)之一。从加速计和PPG传感器中提取了反映运动、呼吸和心率变异性的特征。主要结果：基于LEALEONE-OUT验证，自动算法的总体每纪元准确率为69%，Cohen‘s kappa为0.52+/-0.14。没有明显的偏差低估或高估清醒、轻度或深度睡眠的持续时间。系统略微高估了REM睡眠的持续时间。最常见的错误分类是光/REM和光/尾流标签错误。意义：结果表明，使用手腕佩戴的设备可以达到合理程度的睡眠分期精度，这可能有助于对睡眠习惯的纵向研究。
Objective: This paper aims to report on the accuracy of estimating sleep stages using a wrist-worn device that measures movement using a 3D accelerometer and an optical pulse photoplethysmograph (PPG). Approach: Overnight recordings were obtained from 60 adult participants wearing these devices on their left and right wrist, simultaneously with a Type III home sleep testing device (Embletta MPR) which included EEG channels for sleep staging. The 60 participants were self-reported normal sleepers (36 M: 24 F, age = 34 +/- 10, BMI = 28 +/- 6). The Embletta recordings were scored for sleep stages using AASM guidelines and were used to develop and validate an automated sleep stage estimation algorithm, which labeled sleep stages as one of Wake, Light (N1 or N2), Deep (N3) and REM (REM). Features were extracted from the accelerometer and PPG sensors, which reflected movement, breathing and heart rate variability. Main results: Based on leaveone- out validation, the overall per-epoch accuracy of the automated algorithm was 69%, with a Cohen's kappa of 0.52 +/- 0.14. There was no observable bias to under-or over-estimate wake, light, or deep sleep durations. REM sleep duration was slightly over-estimated by the system. The most common misclassifications were light/REM and light/wake mislabeling. Significance: The results indicate that a reasonable degree of sleep staging accuracy can be achieved using a wrist-worn device, which may be of utility in longitudinal studies of sleep habits.